The impact of Twitter on stock markets

It is well known that the collective mood state of Twitter is correlated to the value of stock market indices such as the Dow Jones Industrial Average (DJIA). Indeed, in some cases Twitter has been the spark of stock market crashes and rallies. For example on April 23rd 2013 a fake tweet was sent out by the hacked account of Associated Press, suggesting that explosions at the White House had injured President Barack Obama. As a result the DJIA dropped about 150 points in a matter of seconds. In another case, on February 19th 2013 the shares of French appliances group Seb soared by 4.08% in a matter of hours, after US television personality Oprah Winfrey told her millions of Twitter followers that its low-oil fryer “had changed my life”.

The objective of the project is analysing similar episodes occurred in the Twittersphere, in order to understand their static (e.g., who initiated it? Which Klout score and number of followers did the initiator have?) and dynamics (e.g., How fast did the episode develop and decay?) characteristics. For that, you will retrieve historical data from Twitter and other sources, align the streams of data to spot correlations, build graphic visualisations to better understand the dynamics. The depth of analysis will depend on your motivation and skills, provided that you are enthusiast and curious to find some initial answers to these questions.

NOTE: this project is already assigned

Prerequisites

• Good knowledge of Object Oriented programming
• Great communication skills

Preferred, but not required

• Some knowledge of a scripting language
• Familiar with basic Machine Learning and Data Mining